Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Darren M. Chan"'
Publikováno v:
ACM Transactions on Human-Robot Interaction. 9:1-21
The robotics community continually strives to create robots that are deployable in real-world environments. Often, robots are expected to interact with human groups. To achieve this goal, we introduce a new method, the Robot-Centric Group Estimation
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e137b690aa546ad5f1eedafe205cddf9
https://doi.org/10.1145/3375798
https://doi.org/10.1145/3375798
Autor:
Darren M. Chan, Laurel D. Riek
Publikováno v:
IEEE Robotics and Automation Letters. 5:1484-1491
A key challenge in robotics is the capability to perceive unseen objects, which can improve a robot's ability to learn from and adapt to its surroundings. One approach is to employ unsupervised, salient object discovery methods, which has shown promi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::206395632cb5aa8f4301d2da253399ed
https://doi.org/10.1109/lra.2020.2968059
https://doi.org/10.1109/lra.2020.2968059
Autor:
Laurel D. Riek, Darren M. Chan
Publikováno v:
IROS
The recent emergence of object proposal algorithms in the computer vision community shows great promise to addressing difficult problems in robotic such as object discovery and salient object detection. However, it is difficult to determine how these
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::746f824e0f6ed0ab6a4c19916eb48ac8
https://doi.org/10.1109/iros40897.2019.8967830
https://doi.org/10.1109/iros40897.2019.8967830
Publikováno v:
IROS
This paper introduces Salient Depth Partitioning (SDP), a depth-based region cropping algorithm devised to be easily adapted to existing detection algorithms. SDP is designed to give robots a better sense of visual attention, and to reduce the proces
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3a0292b4512cb3f51228021c8f836640
https://doi.org/10.1109/iros.2017.8206275
https://doi.org/10.1109/iros.2017.8206275